Ditemukan 20743 dokumen yang sesuai dengan query
Zelle, John
"Introduces computer programming using the Python programming language."
Sherwood, Or.: Franklin, Beedle and Associates, 2010
005.133 ZEL p
Buku Teks SO Universitas Indonesia Library
Lutz, Mark
Beijing : O'Reilly, 1999
005.133 LUT l (1)
Buku Teks Universitas Indonesia Library
Lambert, Kenneth A.
"Publisher Synopsis
1. Introduction. 2. Data Types and Expressions. 3. Control Statements. 4. Strings and Text Files. 5. Lists and Dictionaries. 6. Design with Functions. 7. Simple Graphics and Image Processing. 8. Design with Classes. 9. Graphical User Interfaces. 10. Multithreading, Networks, and Client/Server Programming. 11. Searching, Sorting, and Complexity. (Online only) Appendices. Glossary. Inde"
Australia: Course Technology, Cengage Learning, 2012
005.133 LAM f (1)
Buku Teks Universitas Indonesia Library
Langtangen, Hans Petter
"The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming."
New York: [, Springer-Verlag Berlin Heidelberg], 2012
e20418910
eBooks Universitas Indonesia Library
Annisa Ananta Koesuma
"Penggunaan Python dipilih karena bahasa pemrograman ini bersifat open source dengan banyak tersedianya berbagai sumber dan Python juga diklaim sebagai bahasa yang menggabungkan kapabilitas, dengan kode sintaks yang sangat jelas, dan dilengkapi dengan bahasa yang besar dan komprehensif. Library Open CV juga tersedia secara gratis dan menyediakan banyak fungsi pemrosesan gambar. Pengoreksian citra CBCT yang dilakukan pada penelitian ini bertujuan untuk meningkatkan kualitas citra CBCT dengan melihat meningkatnya nilai yang didapat pada citra CBCT terkoreksi. Phantom CIRS 002LFC di-scan pada CBCT menggunakan half bow tie filter sesuai dengan protokol yang digunakan untuk scanning organ thorax. Penelitian ini menggunakan data citra pasien dengan diagnosa kanker paru dan laring masing-masing berjumlah dua dan satu orang. Hasil kalibrasi CBCT terhadap CT diperoleh bahwa nilai HU citra CBCT linier terhadap citra CT. Evaluasi PSNR dan SSIM digunakan pada penelitian ini sebagai parameter keberhasilan dari citra yang dikoreksi.
Python was chosen because this programming language is open source with many sources available and Python is also claimed to be a language that combines capabilities, with very clear syntax code, and is equipped with a large and complete language. CV Open Library is also available free of charge and provides many drawing functions. CBCT image correction carried out in this study aims to improve the quality of CBCT images by looking at the value obtained in the corrected CBCT image. Phantom CIRS 002LFC was scanned on CBCT using a half bow tie filter according to the protocol used for scanning the thorax organs. This study uses image data of patients diagnosed with lung and laryngeal cancer, respectively, two and one person. The CBCT calibration results against CT showed that the HU value of CBCT images was linear to CT images. PSNR and SSIM evaluations were used in this study as the confidence parameters of the corrected image."
Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2020
S-pdf
UI - Skripsi Membership Universitas Indonesia Library
Ucoluk, Gokturk
"The current text provides a clear introduction to computer science concepts in a programming environment. It is designed as suitable use in freshman- or introductory level coursework in CS and provides the fundamental concepts as well as abstract theorems for solving computational problems. The Python language serves as a medium for illustrating and demonstrating the concepts."
Wien: Springer, 2012
e20406688
eBooks Universitas Indonesia Library
Bassi, Sebastian
Boca Raton: CRC Press, 2018
005.133 BAS p
Buku Teks Universitas Indonesia Library
Addi Ryan
"Pengembangan sistem pendeteksi plagiarisme dibuat untuk mengatasi masalah plagiarisme yang kerap terjadi pada dunia akademis. Pada skripsi ini dibuat sistem pendeteksi plagiarisme otomatis pada karya tulis digital dwi bahasa Indonesia-Inggris dengan Bahasa Indonesia digunakan sebagai karya tulis yang akan diuji dan Bahasa Inggris sebagai karya tulis referensinya. Sistem menerapkan algoritma winnowing yang dilengkapi dengan metode penerjemah bahasa Googletrans API dan similar words. Algoritma winnowing merupakan algoritma yang dapat mendeteksi kesamaan antar teks dengan menggunakan fingerprint yang didapat dari proses hashing karakter teks. Penelitian dilakukan untuk meningkatkan akurasi sistem dan mengetahui metode penilai kesamaan teks yang akurat.
Dari hasil penelitian, didapatkan bahwa parameter terbaik algoritma winnowing secara umum terdapat saat nilai k-window = 5 dan nilai basis bilangan prima bernilai 3. Parameter n-gram bernilai kecil akan lebih akurat pada teks yang memiliki jumlah kata lebih sedikit dan/atau tingkat plagiarisme tinggi dan sebaliknya. Tingkat akurasi sistem pendeteksi plagiarisme otomatis dwi bahasa yang dikembangkan berkisar antara 75.02 hingga 99.51.
Metode Cosine Similarity menjadi metode penilai kesamaan teks terbaik dari hasil penelitian ini. Selain itu, metode penerjemahan Googletrans API juga memberikan kelebihan dalam hal akurasi dan kelengkapan data kamus dibandingkan dengan metode kamus terjemahan database.
The development of plagiarism detection system is made to overcome the problem of plagiarism that often occurs in the academic world. In this thesis, an automatic plagiarism detection system on bilingual digital paper Indonesian English is created with Indonesian is used as the tested paper and English as the reference paper. The system implements the winnowing algorithm that comes with the Googletrans API language translator method and similar words. Winnowing algorithm is an algorithm that can detect similarity between text by using fingerprint obtained from hashing process of text character. The study was conducted to improve system accuracy and to know accurate method of text equality assessment. From the study result, it is found that the best parameter of winnowing algorithm is generally occured when the value of k window 5 and the base value of the prime number is 3. The smaller value of n gram parameter will be more accurate in text that has fewer word counts and or high plagiarism levels and vice versa. The accuracy level of the automatic plagiarism detection system in the developed language ranged from 75.02 to 99.51 . The Cosine Similarity method is the best method of text equality assessment according to results of this study. In addition, the Googletrans API translation method also provides advantages in terms of accuracy and completeness of dictionary data as compared to database translation dictionary method."
Depok: Fakultas Teknik Universitas Indonesia, 2018
S-Pdf
UI - Skripsi Membership Universitas Indonesia Library
Ketkar, Nikhil
"Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process.Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms. This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included. Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. You will: Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe Gain the fundamentals of deep learning with mathematical prerequisites Discover the practical considerations of large scale experiments Take deep learning models to production"
New York: Apress, 2017
005.13 KET d
Buku Teks Universitas Indonesia Library
Stevens, Tim, 1976-
Cambridge : Cambridge University Press, 2015
005.133 STE p
Buku Teks Universitas Indonesia Library